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Author: Olaf Dammann Publisher: Springer ISBN: 3319963074 Category : Medical Languages : en Pages : 139
Book Description
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Author: Olaf Dammann Publisher: Springer ISBN: 3319963074 Category : Medical Languages : en Pages : 139
Book Description
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Author: Olaf Dammann Publisher: ISBN: 9783319963082 Category : Data mining Languages : en Pages : 134
Book Description
Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Author: Jonathan Sholl Publisher: Springer Nature ISBN: 3030526631 Category : Medical Languages : en Pages : 551
Book Description
This edited volume aims to better understand the multifaceted phenomenon we call health. Going beyond simple views of health as the absence of disease or as complete well-being, this book unites scientists and philosophers. The contributions clarify the links between health and adaptation, robustness, resilience, or dynamic homeostasis, and discuss how to achieve health and healthy aging through practices such as hormesis. The book is divided into three parts and a conclusion: the first part explains health from within specific disciplines, the second part explores health from the perspective of a bodily part, system, function, or even the environment in which organisms live, and the final part looks at more clinical or practical perspectives. It thereby gathers, across 30 chapters, diverse perspectives from the broad fields of evolutionary and systems biology, immunology, and biogerontology, more specific areas such as odontology, cardiology, neurology, and public health, as well as philosophical reflections on mental health, sexuality, authenticity and medical theories. The overarching aim is to inform, inspire and encourage intellectuals from various disciplines to assess whether explanations in these disparate fields and across biological levels can be sufficiently systematized and unified to clarify the complexity of health. It will be particularly useful for medical graduates, philosophy graduates and research professionals in the life sciences and general medicine, as well as for upper-level graduate philosophy of science students.
Author: J.A. Magnuson Publisher: Springer Science & Business Media ISBN: 1447142373 Category : Medical Languages : en Pages : 665
Book Description
This revised edition covers all aspects of public health informatics and discusses the creation and management of an information technology infrastructure that is essential in linking state and local organizations in their efforts to gather data for the surveillance and prevention. Public health officials will have to understand basic principles of information resource management in order to make the appropriate technology choices that will guide the future of their organizations. Public health continues to be at the forefront of modern medicine, given the importance of implementing a population-based health approach and to addressing chronic health conditions. This book provides informatics principles and examples of practice in a public health context. In doing so, it clarifies the ways in which newer information technologies will improve individual and community health status. This book's primary purpose is to consolidate key information and promote a strategic approach to information systems and development, making it a resource for use by faculty and students of public health, as well as the practicing public health professional. Chapter highlights include: The Governmental and Legislative Context of Informatics; Assessing the Value of Information Systems; Ethics, Information Technology, and Public Health; and Privacy, Confidentiality, and Security. Review questions are featured at the end of every chapter. Aside from its use for public health professionals, the book will be used by schools of public health, clinical and public health nurses and students, schools of social work, allied health, and environmental sciences.
Author: Maria Lasonen-Aarnio Publisher: Taylor & Francis ISBN: 1317373901 Category : Philosophy Languages : en Pages : 562
Book Description
What one can know depends on one’s evidence. Good scientific theories are supported by evidence. Our experiences provide us with evidence. Any sort of inquiry involves the seeking of evidence. It is irrational to believe contrary to your evidence. For these reasons and more, evidence is one of the most fundamental notions in the field of epistemology and is emerging as a crucial topic across academic disciplines. The Routledge Handbook of the Philosophy of Evidence is an outstanding reference source to the key topics, problems, and debates in this exciting subject and is the first major volume of its kind. Comprising forty chapters by an international team of contributors the handbook is divided into six clear parts: The Nature of Evidence Evidence and Probability The Social Epistemology of Evidence Sources of Evidence Evidence and Justification Evidence in the Disciplines The Routledge Handbook of the Philosophy of Evidence is essential reading for students and researchers in philosophy of science and epistemology, and will also be of interest to those in related disciplines across the humanities and social sciences, such as law, religion, and history.
Author: Kevin McCain Publisher: Routledge ISBN: 1351336614 Category : Philosophy Languages : en Pages : 314
Book Description
What Is Scientific Knowledge? is a much-needed collection of introductory-level chapters on the epistemology of science. Renowned historians, philosophers, science educators, and cognitive scientists have authored 19 original contributions specifically for this volume. The chapters, accessible for students in both philosophy and the sciences, serve as helpful introductions to the primary debates surrounding scientific knowledge. First-year undergraduates can readily understand the variety of discussions in the volume, and yet advanced students and scholars will encounter chapters rich enough to engage their many interests. The variety and coverage in this volume make it the perfect choice for the primary text in courses on scientific knowledge. It can also be used as a supplemental book in classes in epistemology, philosophy of science, and other related areas. Key features: * an accessible and comprehensive introduction to the epistemology of science for a wide variety of students (both undergraduate- and graduate-level) and researchers * written by an international team of senior researchers and the most promising junior scholars * addresses several questions that students and lay people interested in science may already have, including questions about how scientific knowledge is gained, its nature, and the challenges it faces.
Author: Judea Pearl Publisher: John Wiley & Sons ISBN: 1119186862 Category : Mathematics Languages : en Pages : 162
Book Description
CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.
Author: Leo Anthony Celi Publisher: Springer Nature ISBN: 3030479943 Category : Medical Languages : en Pages : 471
Book Description
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Author: R. J. Hankinson Publisher: Oxford University Press ISBN: 0199246564 Category : Literary Collections Languages : en Pages : 516
Book Description
R. J. Hankinson traces the history of ancient Greek thinking about causation and explanation, from its earliest beginnings through more than a thousand years to the middle of the first millennium of the Christian era. He examines ways in which the Ancient Greeks dealt with questions about how and why things happen as and when they do, about the basic constitution and structure of things, about function and purpose, laws of nature, chance, coincidence, and responsibility.
Author: David E Nelson Publisher: Oxford University Press ISBN: 0199700729 Category : Medical Languages : en Pages : 344
Book Description
The demand for health information continues to increase, but the ability of health professionals to provide it clearly remains variable. The aim of this book is (1) to summarize and synthesize research on the selection and presentation of data pertinent to public health, and (2) to provide practical suggestions, based on this research summary and synthesis, on how scientists and other public health practitioners can better communicate data to the public, policy makers, and the press in typical real-world situations. Because communication is complex and no one approach works for all audiences, the authors emphasize how to communicate data "better" (and in some instances, contrast this with how to communicate data "worse"), rather than attempting a cookbook approach. The book contains a wealth of case studies and other examples to illustrate major points, and actual situations whenever possible. Key principles and recommendations are summarized at the end of each chapter. This book will stimulate interest among public health practitioners, scholars, and students to more seriously consider ways they can understand and improve communication about data and other types of scientific information with the public, policy makers, and the press. Improved data communication will increase the chances that evidence-based scientific findings can play a greater role in improving the public's health.
Author: Olaf Dammann
Author: Olaf Dammann
Author: Olaf Dammann
Author: Jonathan Sholl
Author: J.A. Magnuson
Author: Maria Lasonen-Aarnio
Author: Kevin McCain
Author: Judea Pearl
Author: Leo Anthony Celi
Author: R. J. Hankinson
Author: David E Nelson